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Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

BACKGROUND: Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage who...

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Autores principales: Delomas, Thomas A., Willis, Stuart C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623847/
https://www.ncbi.nlm.nih.gov/pubmed/37923981
http://dx.doi.org/10.1186/s12859-023-05554-z
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author Delomas, Thomas A.
Willis, Stuart C.
author_facet Delomas, Thomas A.
Willis, Stuart C.
author_sort Delomas, Thomas A.
collection PubMed
description BACKGROUND: Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data. RESULTS: We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing. CONCLUSIONS: These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05554-z.
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spelling pubmed-106238472023-11-04 Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data Delomas, Thomas A. Willis, Stuart C. BMC Bioinformatics Research BACKGROUND: Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data. RESULTS: We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing. CONCLUSIONS: These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05554-z. BioMed Central 2023-11-03 /pmc/articles/PMC10623847/ /pubmed/37923981 http://dx.doi.org/10.1186/s12859-023-05554-z Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Delomas, Thomas A.
Willis, Stuart C.
Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title_full Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title_fullStr Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title_full_unstemmed Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title_short Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
title_sort estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623847/
https://www.ncbi.nlm.nih.gov/pubmed/37923981
http://dx.doi.org/10.1186/s12859-023-05554-z
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